Unsupervised clustering of spectral signatures in Landsat imagery : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Computer Science at Massey University

Abstract

This thesis describes an investigation into automatic recognition of satellite imagery from the LANDSAT Project. Clustering techniques are shown to be the most suitable; of the three clustering algorithms investigated the k-means is shown to be the most effective. The need to perform edge detection on the images prior to clustering is also demonstrated. A suitable algorithm for edge detection is described. Indexing terms: clustering, LANDSAT Satellite project, pattern recognition, Satellite data